Search Results

The AKITA2 APIXNEB is a nebulizer system that will be used with patients for whom doctors have prescribed medication (except pentamidine) for nebulization in the home care, nursing home, sub-acute institution, or hospital environment.
The AKITA2 APIXNEB is intended for patients 3 years and older who can coordinate breathing.

The AKITA? APIXNEB nebulizer and the handset together constitute a single patient, multi-use, electronic nebulizer system designed to aerosolize liquid medications. The system includes and features:

• An electrically powered compressor which provides an air flow to the AKITA2 . APIXNEB nebulizer handset.
• . A nebulizer handset based upon the PARI e-Flow™, K033833, which uses piezoelectric vibration of a perforated stainless steel membrane (head) for the aerosol generation.
• . Single patient use, reusable
• Nebulization only during inhalation phase .
• . Smart Card series for defined patient breathing patterns

The provided text describes the AKITA2 APIXNEB nebulizer system and its substantial equivalence to predicate devices, but it does not contain information about acceptance criteria for a study proving device performance in the context of an AI/ML medical device, nor does it detail a study methodology as requested.

The document is a 510(k) premarket notification for a traditional medical device (a nebulizer), not an AI/ML-driven device. Therefore, many of the requested categories related to AI/ML evaluations (such as sample sizes for test/training sets, expert ground truth establishment, MRMC studies, or standalone algorithm performance) are not applicable or present in this submission.

The document discusses "safety and effectiveness testing" which includes various performance tests (e.g., flow performance, trigger pressure performance, nebulization time performance), but it does not specify acceptance criteria for these tests nor does it provide a report of the device's performance against specific numerical or qualitative targets. Instead, it states that these tests were "done" to demonstrate substantial equivalence and safety/effectiveness.

Therefore, many of the requested fields cannot be populated from the provided text.

Here's an attempt to fill in the table based on the available information, with many fields noted as "Not applicable" or "Not provided."

Acceptance Criteria and Reported Device Performance

Study Details (AI/ML Specific - Not applicable to this device)

1. Sample size used for the test set and the data provenance: Not applicable; this is a traditional medical device, not an AI/ML device. No test set for an algorithm is mentioned.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable; no ground truth for an AI/ML model test set is discussed.
3. Adjudication method for the test set: Not applicable; no test set for an AI/ML algorithm is mentioned.
4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: Not applicable; this is not an AI-assisted device.
5. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable; this is not an AI-driven device.
6. The type of ground truth used: For traditional device performance tests, the "ground truth" would be established by validated measurement techniques and adherence to industry standards, but specific methodologies and validation for each test are not detailed in this summary. It's not clinical ground truth (e.g., pathology, outcomes).
7. The sample size for the training set: Not applicable; this is a traditional medical device, not an AI/ML device.
8. How the ground truth for the training set was established: Not applicable; no training set for an AI/ML model is discussed.

Summary of available information:

The K072019 submission for the AKITA2 APIXNEB nebulizer system focuses on demonstrating substantial equivalence to existing predicate devices (I-neb Insight, ProDose, eFlow™, AutoNeb). The device is a traditional nebulizer, not an AI/ML-driven medical device.

To support substantial equivalence and claims of safety and effectiveness, a series of performance tests were conducted, including:

• Flow performance
• Trigger Pressure performance
• On/Off performance
• Nebulization Time performance
• Time lag performance
• Timing Parameters
• Life Time test
• Cleaning performance
• Smart Card performance
• Inhalation / Exhalation resistance
• VOC and PM25 testing
• Electrical safety, EMC, EMI, Mechanical and environmental testing

The document states that these tests were performed, and the conclusion is that "There are no significant differences that affect the safety or effectiveness of the intended device as compared to the predicate devices." This implies that the device performed acceptably in these tests, aligning with the performance of the predicate devices. However, specific acceptance criteria (e.g., numerical ranges, pass/fail thresholds) and the detailed results of these tests are not provided in this non-confidential summary. The study design and results are presented as foundational for the "substantial equivalence" claim rather than a detailed report against specific performance criteria.

Ask a specific question about this device